Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	36457
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	5.6 MiB
Average record size in memory	160.0 B

Variable types

Numeric	10
Categorical	10

Alerts

`Unnamed: 0` is highly correlated with `ID`	High correlation
`ID` is highly correlated with `Unnamed: 0`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`NAME_FAMILY_STATUS` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 1 other fields	High correlation
`Unnamed: 0` is highly correlated with `ID`	High correlation
`ID` is highly correlated with `Unnamed: 0`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`NAME_FAMILY_STATUS` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 1 other fields	High correlation
`Unnamed: 0` is highly correlated with `ID`	High correlation
`ID` is highly correlated with `Unnamed: 0`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`NAME_FAMILY_STATUS` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN` and 1 other fields	High correlation
`Unnamed: 0` is highly correlated with `ID`	High correlation
`ID` is highly correlated with `Unnamed: 0`	High correlation
`CODE_GENDER` is highly correlated with `FLAG_OWN_CAR` and 1 other fields	High correlation
`FLAG_OWN_CAR` is highly correlated with `CODE_GENDER`	High correlation
`CNT_CHILDREN` is highly correlated with `CNT_FAM_MEMBERS`	High correlation
`NAME_INCOME_TYPE` is highly correlated with `OCCUPATION_TYPE` and 2 other fields	High correlation
`OCCUPATION_TYPE` is highly correlated with `CODE_GENDER` and 1 other fields	High correlation
`CNT_FAM_MEMBERS` is highly correlated with `CNT_CHILDREN`	High correlation
`AGE` is highly correlated with `NAME_INCOME_TYPE`	High correlation
`YEARS_EMPLOYED` is highly correlated with `NAME_INCOME_TYPE`	High correlation
`Unnamed: 0` is uniformly distributed	Uniform
`Unnamed: 0` has unique values	Unique
`ID` has unique values	Unique
`CNT_CHILDREN` has 25201 (69.1%) zeros	Zeros
`OCCUPATION_TYPE` has 1241 (3.4%) zeros	Zeros
`YEARS_EMPLOYED` has 6135 (16.8%) zeros	Zeros

Reproduction

Analysis started	2022-04-25 13:54:03.049401
Analysis finished	2022-04-25 13:54:46.702006
Duration	43.65 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Unnamed: 0
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	36457
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18228

Minimum	0
Maximum	36456
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1822.8
Q1	9114
median	18228
Q3	27342
95-th percentile	34633.2
Maximum	36456
Range	36456
Interquartile range (IQR)	18228

Descriptive statistics

Standard deviation	10524.37372
Coefficient of variation (CV)	0.5773740245
Kurtosis	-1.2
Mean	18228
Median Absolute Deviation (MAD)	9114
Skewness	0
Sum	664538196
Variance	110762442.2
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
24307	1	< 0.1%
24301	1	< 0.1%
24302	1	< 0.1%
24303	1	< 0.1%
24304	1	< 0.1%
24305	1	< 0.1%
24306	1	< 0.1%
24308	1	< 0.1%
24299	1	< 0.1%
Other values (36447)	36447	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
36456	1	< 0.1%
36455	1	< 0.1%
36454	1	< 0.1%
36453	1	< 0.1%
36452	1	< 0.1%
36451	1	< 0.1%
36450	1	< 0.1%
36449	1	< 0.1%
36448	1	< 0.1%
36447	1	< 0.1%

ID
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	36457
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5078226.997

Minimum	5008804
Maximum	5150487
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	5008804
5-th percentile	5018456.6
Q1	5042028
median	5074614
Q3	5115396
95-th percentile	5146024.2
Maximum	5150487
Range	141683
Interquartile range (IQR)	73368

Descriptive statistics

Standard deviation	41875.24079
Coefficient of variation (CV)	0.008246035637
Kurtosis	-1.212613663
Mean	5078226.997
Median Absolute Deviation (MAD)	38093
Skewness	0.08624228966
Sum	1.851369216 × 10¹¹
Variance	1753535791
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5008804	1	< 0.1%
5096993	1	< 0.1%
5096983	1	< 0.1%
5096987	1	< 0.1%
5096988	1	< 0.1%
5096990	1	< 0.1%
5096991	1	< 0.1%
5096992	1	< 0.1%
5096994	1	< 0.1%
5096978	1	< 0.1%
Other values (36447)	36447	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5008804	1	< 0.1%
5008805	1	< 0.1%
5008806	1	< 0.1%
5008808	1	< 0.1%
5008809	1	< 0.1%
5008810	1	< 0.1%
5008811	1	< 0.1%
5008812	1	< 0.1%
5008813	1	< 0.1%
5008814	1	< 0.1%

Value	Count	Frequency (%)
5150487	1	< 0.1%
5150485	1	< 0.1%
5150484	1	< 0.1%
5150483	1	< 0.1%
5150482	1	< 0.1%
5150481	1	< 0.1%
5150480	1	< 0.1%
5150479	1	< 0.1%
5150478	1	< 0.1%
5150477	1	< 0.1%

CODE_GENDER
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	24430
1	12027

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	24430	67.0%
1	12027	33.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	24430	67.0%
1	12027	33.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_OWN_CAR
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	22614
1	13843

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	22614	62.0%
1	13843	38.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	22614	62.0%
1	13843	38.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_OWN_REALTY
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

1	24506
0	11951

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	24506	67.2%
0	11951	32.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	24506	67.2%
0	11951	32.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

CNT_CHILDREN
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4303151658

Minimum	0
Maximum	19
Zeros	25201
Zeros (%)	69.1%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	19
Range	19
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.7423669007
Coefficient of variation (CV)	1.7251702
Kurtosis	22.56243396
Mean	0.4303151658
Median Absolute Deviation (MAD)	0
Skewness	2.569382202
Sum	15688
Variance	0.5511086153
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	25201	69.1%
1	7492	20.6%
2	3256	8.9%
3	419	1.1%
4	63	0.2%
5	20	0.1%
14	3	< 0.1%
7	2	< 0.1%
19	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	25201	69.1%
1	7492	20.6%
2	3256	8.9%
3	419	1.1%
4	63	0.2%
5	20	0.1%
7	2	< 0.1%
14	3	< 0.1%
19	1	< 0.1%

Value	Count	Frequency (%)
19	1	< 0.1%
14	3	< 0.1%
7	2	< 0.1%
5	20	0.1%
4	63	0.2%
3	419	1.1%
2	3256	8.9%
1	7492	20.6%
0	25201	69.1%

AMT_INCOME_TOTAL
Real number (ℝ_≥0)

Distinct	265
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	186685.7367

Minimum	27000
Maximum	1575000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	27000
5-th percentile	76500
Q1	121500
median	157500
Q3	225000
95-th percentile	360000
Maximum	1575000
Range	1548000
Interquartile range (IQR)	103500

Descriptive statistics

Standard deviation	101789.2265
Coefficient of variation (CV)	0.5452437251
Kurtosis	17.59808418
Mean	186685.7367
Median Absolute Deviation (MAD)	45000
Skewness	2.739009876
Sum	6806001902
Variance	1.036104663 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
135000	4309	11.8%
180000	3097	8.5%
157500	3089	8.5%
112500	2956	8.1%
225000	2926	8.0%
202500	2192	6.0%
90000	1769	4.9%
270000	1675	4.6%
315000	1001	2.7%
67500	873	2.4%
Other values (255)	12570	34.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
27000	3	< 0.1%
29250	7	< 0.1%
30150	3	< 0.1%
31500	16	< 0.1%
31531.5	3	< 0.1%
31950	1	< 0.1%
32400	5	< 0.1%
33300	10	< 0.1%
33750	1	< 0.1%
36000	5	< 0.1%

Value	Count	Frequency (%)
1575000	8	< 0.1%
1350000	6	< 0.1%
1125000	3	< 0.1%
990000	4	< 0.1%
945000	4	< 0.1%
900000	39	0.1%
810000	15	< 0.1%
787500	5	< 0.1%
765000	9	< 0.1%
742500	5	< 0.1%

NAME_INCOME_TYPE
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

4	18819
0	8490
1	6152
2	2985
3	11

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	4
2nd row	4
3rd row	4
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
4	18819	51.6%
0	8490	23.3%
1	6152	16.9%
2	2985	8.2%
3	11	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
4	18819	51.6%
0	8490	23.3%
1	6152	16.9%
2	2985	8.2%
3	11	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_EDUCATION_TYPE
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

4	24777
1	9864
2	1410
3	374
0	32

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	4
4th row	4
5th row	4

Common Values

Value	Count	Frequency (%)
4	24777	68.0%
1	9864	27.1%
2	1410	3.9%
3	374	1.0%
0	32	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
4	24777	68.0%
1	9864	27.1%
2	1410	3.9%
3	374	1.0%
0	32	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_FAMILY_STATUS
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

1	25048
3	4829
0	2945
2	2103
4	1532

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	3
5th row	3

Common Values

Value	Count	Frequency (%)
1	25048	68.7%
3	4829	13.2%
0	2945	8.1%
2	2103	5.8%
4	1532	4.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	25048	68.7%
3	4829	13.2%
0	2945	8.1%
2	2103	5.8%
4	1532	4.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

NAME_HOUSING_TYPE
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.282881203

Minimum	0
Maximum	5
Zeros	168
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	4
Maximum	5
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.9516747501
Coefficient of variation (CV)	0.7418260929
Kurtosis	9.496421527
Mean	1.282881203
Median Absolute Deviation (MAD)	0
Skewness	3.290847045
Sum	46770
Variance	0.9056848299
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	32548	89.3%
5	1776	4.9%
2	1128	3.1%
4	575	1.6%
3	262	0.7%
0	168	0.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	168	0.5%
1	32548	89.3%
2	1128	3.1%
3	262	0.7%
4	575	1.6%
5	1776	4.9%

Value	Count	Frequency (%)
5	1776	4.9%
4	575	1.6%
3	262	0.7%
2	1128	3.1%
1	32548	89.3%
0	168	0.5%

FLAG_WORK_PHONE
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	28235
1	8222

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	28235	77.4%
1	8222	22.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	28235	77.4%
1	8222	22.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_PHONE
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	25709
1	10748

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	25709	70.5%
1	10748	29.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	25709	70.5%
1	10748	29.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

FLAG_EMAIL
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	33186
1	3271

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	33186	91.0%
1	3271	9.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	33186	91.0%
1	3271	9.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

OCCUPATION_TYPE
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	19
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.170529665

Minimum	0
Maximum	18
Zeros	1241
Zeros (%)	3.4%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	6
median	10
Q3	12
95-th percentile	15
Maximum	18
Range	18
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.292975215
Coefficient of variation (CV)	0.4681272916
Kurtosis	-0.7087343605
Mean	9.170529665
Median Absolute Deviation (MAD)	2
Skewness	-0.437895487
Sum	334330
Variance	18.42963619
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
12	11323	31.1%
8	6211	17.0%
3	3591	9.8%
15	3485	9.6%
10	3012	8.3%
4	2138	5.9%
6	1383	3.8%
0	1241	3.4%
11	1207	3.3%
2	655	1.8%
Other values (9)	2211	6.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1241	3.4%
1	551	1.5%
2	655	1.8%
3	3591	9.8%
4	2138	5.9%
5	85	0.2%
6	1383	3.8%
7	60	0.2%
8	6211	17.0%
9	175	0.5%

Value	Count	Frequency (%)
18	174	0.5%
17	592	1.6%
16	151	0.4%
15	3485	9.6%
14	79	0.2%
13	344	0.9%
12	11323	31.1%
11	1207	3.3%
10	3012	8.3%
9	175	0.5%

CNT_FAM_MEMBERS
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.198452972

Minimum	1
Maximum	20
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	3
95-th percentile	4
Maximum	20
Range	19
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.9116861437
Coefficient of variation (CV)	0.4146944034
Kurtosis	8.188695361
Mean	2.198452972
Median Absolute Deviation (MAD)	0
Skewness	1.298595907
Sum	80149
Variance	0.8311716246
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2	19463	53.4%
1	6987	19.2%
3	6421	17.6%
4	3106	8.5%
5	397	1.1%
6	58	0.2%
7	19	0.1%
15	3	< 0.1%
9	2	< 0.1%
20	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	6987	19.2%
2	19463	53.4%
3	6421	17.6%
4	3106	8.5%
5	397	1.1%
6	58	0.2%
7	19	0.1%
9	2	< 0.1%
15	3	< 0.1%
20	1	< 0.1%

Value	Count	Frequency (%)
20	1	< 0.1%
15	3	< 0.1%
9	2	< 0.1%
7	19	0.1%
6	58	0.2%
5	397	1.1%
4	3106	8.5%
3	6421	17.6%
2	19463	53.4%
1	6987	19.2%

AGE
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	7183
Distinct (%)	19.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	43.73853914

Minimum	20.50418558
Maximum	68.86383704
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	20.50418558
5-th percentile	27.03409379
Q1	34.11979712
median	42.61004675
Q3	53.2194364
95-th percentile	63.02388139
Maximum	68.86383704
Range	48.35965146
Interquartile range (IQR)	19.09963928

Descriptive statistics

Standard deviation	11.50071512
Coefficient of variation (CV)	0.2629423696
Kurtosis	-1.045643576
Mean	43.73853914
Median Absolute Deviation (MAD)	9.377331499
Skewness	0.1842296496
Sum	1594575.921
Variance	132.2664484
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
34.70570922	54	0.1%
42.48957884	54	0.1%
46.25967679	38	0.1%
40.15688207	37	0.1%
41.45191209	32	0.1%
45.90922469	32	0.1%
42.91669233	32	0.1%
38.70305345	30	0.1%
37.75026181	30	0.1%
27.87736915	29	0.1%
Other values (7173)	36089	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
20.50418558	1	< 0.1%
21.09557349	1	< 0.1%
21.14485581	2	< 0.1%
21.23794465	4	< 0.1%
21.79100187	2	< 0.1%
21.84849792	1	< 0.1%
22.01551024	4	< 0.1%
22.05110303	1	< 0.1%
22.05657885	2	< 0.1%
22.08669583	1	< 0.1%

Value	Count	Frequency (%)
68.86383704	2	< 0.1%
68.83098216	3	< 0.1%
68.71872797	1	< 0.1%
68.68861099	1	< 0.1%
68.47505424	2	< 0.1%
68.36553796	2	< 0.1%
68.34637262	1	< 0.1%
68.2998282	3	< 0.1%
68.2614975	4	< 0.1%
68.21221517	3	< 0.1%

YEARS_EMPLOYED
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	3640
Distinct (%)	10.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.024263792

Minimum	0
Maximum	43.0207328
Zeros	6135
Zeros (%)	16.8%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1.117066059
median	4.249231675
Q3	8.632620793
95-th percentile	19.72661999
Maximum	43.0207328
Range	43.0207328
Interquartile range (IQR)	7.515554734

Descriptive statistics

Standard deviation	6.480069439
Coefficient of variation (CV)	1.075661635
Kurtosis	3.847041793
Mean	6.024263792
Median Absolute Deviation (MAD)	3.583920272
Skewness	1.758767075
Sum	219626.5851
Variance	41.99129994
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6135	16.8%
1.09790071	78	0.2%
4.213638884	64	0.2%
0.5475814014	63	0.2%
4.594207958	61	0.2%
5.714011924	61	0.2%
6.929642635	56	0.2%
1.259437223	54	0.1%
3.175972128	53	0.1%
5.631874713	52	0.1%
Other values (3630)	29780	81.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	6135	16.8%
0.04654441912	3	< 0.1%
0.1177300013	1	< 0.1%
0.1779639555	2	< 0.1%
0.1807018625	1	< 0.1%
0.1916534905	4	< 0.1%
0.1943913975	1	< 0.1%
0.1998672115	17	< 0.1%
0.2135567465	1	< 0.1%
0.2162946536	1	< 0.1%

Value	Count	Frequency (%)
43.0207328	1	< 0.1%
42.87836164	4	< 0.1%
41.69011	1	< 0.1%
41.26573441	3	< 0.1%
41.17264557	16	< 0.1%
40.75922161	6	< 0.1%
40.54840277	8	< 0.1%
40.45257603	2	< 0.1%
39.79821625	4	< 0.1%
39.62572811	6	< 0.1%

STATUS
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	284.9 KiB

0	27711
-1	4455
1	4291

Length

Max length	2
Median length	1
Mean length	1.122198755
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	-1

Common Values

Value	Count	Frequency (%)
0	27711	76.0%
-1	4455	12.2%
1	4291	11.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	27711	76.0%
1	8746	24.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

MONTHS_BALANCE
Real number (ℝ_≥0)

Distinct	61
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26.16419343

Minimum	0
Maximum	60
Zeros	315
Zeros (%)	0.9%
Negative	0
Negative (%)	0.0%
Memory size	284.9 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	12
median	24
Q3	39
95-th percentile	55
Maximum	60
Range	60
Interquartile range (IQR)	27

Descriptive statistics

Standard deviation	16.50185447
Coefficient of variation (CV)	0.6307037329
Kurtosis	-1.037761862
Mean	26.16419343
Median Absolute Deviation (MAD)	14
Skewness	0.2863945674
Sum	953868
Variance	272.3112008
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
7	889	2.4%
11	828	2.3%
6	824	2.3%
8	820	2.2%
5	816	2.2%
17	807	2.2%
3	800	2.2%
10	798	2.2%
16	785	2.2%
15	774	2.1%
Other values (51)	28316	77.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	315	0.9%
1	551	1.5%
2	643	1.8%
3	800	2.2%
4	765	2.1%
5	816	2.2%
6	824	2.3%
7	889	2.4%
8	820	2.2%
9	770	2.1%

Value	Count	Frequency (%)
60	321	0.9%
59	307	0.8%
58	333	0.9%
57	304	0.8%
56	345	0.9%
55	368	1.0%
54	358	1.0%
53	377	1.0%
52	463	1.3%
51	476	1.3%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Unnamed: 0	ID	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	AMT_INCOME_TOTAL	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	FLAG_WORK_PHONE	FLAG_PHONE	FLAG_EMAIL	OCCUPATION_TYPE	CNT_FAM_MEMBERS	AGE	YEARS_EMPLOYED	STATUS	MONTHS_BALANCE
0	0	5008804	1	1	1	427500.0	4	1	0	4	1	0	0	12	2	32.868574	12.435574	1	15
1	1	5008805	1	1	1	427500.0	4	1	0	4	1	0	0	12	2	32.868574	12.435574	1	14
2	2	5008806	1	1	1	112500.0	4	4	1	1	0	0	0	17	2	58.793815	3.104787	0	29
3	3	5008808	0	0	1	270000.0	0	4	3	1	0	1	1	15	1	52.321403	8.353354	0	4
4	4	5008809	0	0	1	270000.0	0	4	3	1	0	1	1	15	1	52.321403	8.353354	-1	26
5	5	5008810	0	0	1	270000.0	0	4	3	1	0	1	1	15	1	52.321403	8.353354	0	26
6	6	5008811	0	0	1	270000.0	0	4	3	1	0	1	1	15	1	52.321403	8.353354	0	38
7	7	5008812	0	0	1	283500.0	1	1	2	1	0	0	0	12	1	61.504343	0.000000	0	20
8	8	5008813	0	0	1	283500.0	1	1	2	1	0	0	0	12	1	61.504343	0.000000	0	16
9	9	5008814	0	0	1	283500.0	1	1	2	1	0	0	0	12	1	61.504343	0.000000	0	17

Last rows

	Unnamed: 0	ID	CODE_GENDER	FLAG_OWN_CAR	FLAG_OWN_REALTY	CNT_CHILDREN	AMT_INCOME_TOTAL	NAME_INCOME_TYPE	NAME_EDUCATION_TYPE	NAME_FAMILY_STATUS	NAME_HOUSING_TYPE	FLAG_WORK_PHONE	FLAG_PHONE	FLAG_EMAIL	OCCUPATION_TYPE	CNT_FAM_MEMBERS	AGE	YEARS_EMPLOYED	STATUS	MONTHS_BALANCE
36447	36447	5149145	1	1	1	0	247500.0	4	4	1	1	1	0	0	8	2	29.985558	9.793493	1	25
36448	36448	5149158	1	1	1	0	247500.0	4	4	1	1	1	0	0	8	2	29.985558	9.793493	1	28
36449	36449	5149190	1	1	0	1	450000.0	4	1	1	1	0	1	1	3	3	26.960170	1.374429	1	11
36450	36450	5149729	1	1	1	0	90000.0	4	4	1	1	0	0	0	12	2	52.296762	4.711938	1	21
36451	36451	5149775	0	1	1	0	130500.0	4	4	1	1	0	1	0	8	2	44.181605	25.711685	1	19
36452	36452	5149828	1	1	1	0	315000.0	4	4	1	1	0	0	0	10	2	47.497211	6.625735	1	11
36453	36453	5149834	0	0	1	0	157500.0	0	1	1	1	0	1	1	11	2	33.914454	3.627727	1	23
36454	36454	5149838	0	0	1	0	157500.0	1	1	1	1	0	1	1	11	2	33.914454	3.627727	1	32
36455	36455	5150049	0	0	1	0	283500.0	4	4	1	1	0	0	0	15	2	49.167334	1.793329	1	9
36456	36456	5150337	1	0	1	0	112500.0	4	4	3	4	0	0	0	8	1	25.155890	3.266323	1	13

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script